Exploring urban lifestyles using a nonparametric temporal graphical model

Jameel, Shoaib, Liao, Yi, Lam, Wai, Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 and Xie, Xing 2016. Exploring urban lifestyles using a nonparametric temporal graphical model. Presented at: ACM International Conference on the Theory of Information Retrieval, Newark, DE, USA, 13-16 September 2016.

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Abstract

We propose a new unsupervised nonparametric temporal topic model to discover lifestyle patterns from location-based social networks. By relating the textual content, time stamps, and venue categories associated to user check-ins, our framework detects the predominant lifestyle patterns in a given geographic region. The temporal component of our model allows us to analyse the evolution of lifestyle patterns throughout the year. We provide examples of interesting patterns that have been discovered by our model, and we show that our model compares favourably to existing approaches in terms of lifestyle pattern quality and computation time. We also quantitatively show that our model outperforms existing methods in a time stamp prediction task.

Item Type:	Conference or Workshop Item (Paper)
Status:	Unpublished
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Funders:	Research Grant Council of the Hong Kong Special Administrative Region, ERC, Direct Grant of the Faculty of Engineering, CUHK
Date of First Compliant Deposit:	12 December 2017
Last Modified:	01 Nov 2022 10:55
URI:	https://orca.cardiff.ac.uk/id/eprint/93261

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